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2018 has kicked off to a great start for us at Stage. We are in talks with Bike Share operators around the world and looking to deploy our BICO solution in new markets abroad.

We recently launched in Guadalajara, the second largest city in Mexico. Our AI platform is being used to optimise and automate Bike Share management across the city.

We are also currently in the final stages with one of the leading Bike Share operators in Europe. We look forward to releasing the news in the coming months and keeping you updated with what’s happening at Stage.

If you’d like to know more about our deployments or to find out what’s in the pipeline, please get in touch.

http://stageintelligence.co.uk/wp-content/uploads/2018/02/90bff8ba-74e6-4b0e-ac65-ef4947d2ac69.png3571024stageintelligencehttp://stageintelligence.co.uk/wp-content/uploads/2017/05/Si-logo_long.pngstageintelligence2018-02-08 09:14:052018-02-08 09:26:22Stage Kicks Off 2018 with a New Deployment in Latin America

2018 will be the tipping point for Artificial Intelligence (AI) in the transportation industry. It will be a year where AI becomes an essential tool with new understanding and recognition that it is critical to success. In our business and beyond, we’ve seen how influential this technology can be in changing business models and creating better transport solutions.

At Stage Intelligence, we’re seeing this become a reality. In 2017, we’ve seen tremendous momentum behind our business and growing demand for real AI solutions in transportation. We’re rolling out our AI-based Bike Share management solution in cities across the globe and changing the perception that Bike Share isn’t a viable, reliable transport option.

We are helping to accelerate transformation in transportation and utilising self-organising algorithms and elements of machine learning to simplify and empower Bike Share management.

2018: Challenges in AI

The future of transportation will be defined by AI. Research firm Gartner predicts that by 2020 almost every new software product will have AI technologies. In transportation, we are starting to see widespread application and development of AI technology that is being powered by the collection of data and use of algorithms.

That said, it is still a very young market with challenges ahead. I see three big challenges for AI in transportation:

Not All “AI” is the Same – Many businesses that say they use AI don’t actually have it deployed. It is a buzzword and many businesses are doing data visualisations or pretty interfaces but when you look under the hood there’s nothing there. Operators eager to benefit from AI don’t get what they paid for and won’t see the best of it.

Transportation Expertise and Focus – AI solutions need to address specific challenges. They need to be purpose built for transportation and developed by both experts in transportation and AI. Otherwise, you get generic solutions that solve generic problems rather than enabling real innovation and agility in transportation.

Nurturing AI – AI isn’t just about building solutions. It is about training it and nurturing it to deliver the results you want. It requires people, time, effort and a lot of data to continuously maintain and develop the technology. You don’t just flip a switch. It requires an expert experienced in developing and growing successful solutions.

As we see more AI-based solutions adopted, there will be a move towards quality and performance. Solutions that are based more on buzzwords than results will fade away.

In 2018, more people will understand the basics of AI and make better decisions about the solutions they deploy. That’s good for transportation and will accelerate its growth.

Building Better Bike Share Schemes

We’ve seen tremendous growth in our business over the past year. In 2017, we deployed our solutions in new corners of the world.

Our business development team led by Tom Nutley was out and about at events and meetings almost on a monthly basis. We’ve been successful in sharing our belief in automated rebalancing and using self-organising algorithms to build better Bike Share Schemes and that has led to trials and deployments around the world.

Our flagship BICO Bike Share Scheme management platform has been adopted and is supporting ridership growth in unique markets in the Americas and Europe. In 2017, We added greater functionality to BICO including a successful internationalisation process that helped us to better serve our partners abroad and dynamic replenishment values for greater predictive management of a scheme. Both have made it easier for operators to deploy and benefit from our solution.

We are also proud to have partnered with industry bodies to accelerate transformation in Bike Share Schemes. We are a member of the platform for European Bicycle Sharing & Systems (PEBSS), created by European Cyclist’s Federation (ECF). Our work with ECF and PEBSS highlights our commitment to growing a healthier cycling market for all.

In November, our usability data was shared around the world and is influencing conversation about how to create Bike Share Schemes that give riders an optimised experience. We are sharing our data and analytics to show what is possible in Bike Share when you take a new approach.

This Time Next Year

Throughout 2018, we will develop our AI technology for the shared mobility market, innovate for Bike Share operators and continue to roll our solutions around the world. It is an exciting time for our industry and we are ready to help our partners benefit from our solution and encourage the continued growth of Bike Share.

As cities around the globe continue to push towards cleaner and more sustainable transportation, we will see increased demand for user-friendly Biker Share. How cities and operators manage their schemes and support riders will define their success.

The tipping point in Bike Share will be seen when automated rebalancing becomes a critical part of any Bike Share operator’s conversations about growth. AI will at least be considered when discussing a path forward for schemes looking to grow. That’s a big step forward in an industry that is constantly changing.

There are a few things that I believe will define the Bike Share in 2018:

Growing Bike Share Schemes

As more Bike Shares use AI-based management solutions, riders will get a better experience and schemes will grow. It will enable faster decision making for bike distribution, ensuring that riders get bikes and docks where and when they need them. That drives growth and creates new efficiencies.

Move Towards Electric

We will see a greater push in electric cars, bikes and scooters in an effort to reduce emissions and drive down costs. We will see more Bike Share offering e-bikes and even further introduction of e-scooter sharing in cities around the world. With greater range and a larger, more diverse user base, schemes will need better management solutions to drive efficiency.

Mobility as a Service

We will see mobile phones play a greater role in traditional transportation. Mobility as Service (MaaS) showed its potential in 2017 and now MaaS will begin being rolled out in cities around the globe. It will streamline how we travel and deliver even more data about how we commute.

The End of the Free-For-All in Free Floating

The free-for-all in Free Floating Bike Share has to come to an end. Healthy markets do not tolerate massive oversupply and as we’ve seen in some cities in China it leads to failing schemes. Free Floating Bike Share Schemes need to be managed and follow policies set out by local governments to be successful. In 2018, we hope to see less mistakes made and a lesson to be learned.

All of these things will drive demand for AI-based solutions and the evolution of Bike Share Scheme management. Bike Share operations should be simpler to manage with better experiences for riders. In 2018, we will solve some of the challenges in transportation and deliver solutions that benefit cities, citizens and the environment. I see tremendous potential in our business and our industry. 2018 will be a phenomenal year for AI in transportation.

http://stageintelligence.co.uk/wp-content/uploads/2018/01/AI-City.jpg6001170stageintelligencehttp://stageintelligence.co.uk/wp-content/uploads/2017/05/Si-logo_long.pngstageintelligence2018-01-04 11:51:122018-01-04 11:51:472018: A Tipping Point for Artificial Intelligence in Transportation

Big data is changing how we experience cities and enabling us to live healthier, happier and more productive lives. As cities become smarter, big data is being used to reimagine transportation and how we get from A to B.

Every city is producing vast amounts of data every hour and every day. Increasingly this data is being captured and put to work creating new solutions, processes and experiences that improve how a city functions and is enjoyed by citizens.

Data can be used to improve, urban planning, health care, sustainability, transportation and just about every aspect of a city. The “smart” in Smart Cities is about taking this data and rapidly turning it into actionable insights.

According to IBM, a Smart City “makes optimal use of all the interconnected information available today to better understand and control its operations and optimise the use of limited resources”. It makes cities better places to live and enables the best use of what a city’s budgets, space, people and technologies.

By 2021, open and shared data has the potential to add $2.83 billion (10.4 Billion AED) to Dubai’s economy every year, according to a report produced by KPMG. That is a lasting and long-term impact on the city of Dubai and results from using data in a Smart City environment.

While Smart City deployments continue to grow, transportation is an area where we are already seeing the direct impact of data on how citizens live day-to-day. In modern cities, Bike Share Schemes have emerged as a healthy and efficient means of commuting and navigating a city.

These schemes are taking the Smart City concept and applying it to local challenges and succeeding in growing ridership and providing more citizens with healthy and efficient transportation.

It’s this citywide data that is at the heart of the three pillars of smarter public bike sharing system as set out in the Policy Framework for Smart Public-Use Bike Share by the Platform for European Bicycle Sharing & Systems (PEBSS). Data influences how rider priorities are met and how cities offer suitable conditions with sustainable technologies and innovation. Smart Cities support Bike Share Schemes by considering the people, infrastructure and technology elements.

To make data work for Bike Share Scheme operators, it needs to be collected, managed and analysed effectively. This is where Artificial Intelligence (AI) plays a crucial role. AI-based platform manages all available data to deliver valuable insights to operators. The illustration below highlights this.

Insights from schemes in London, Paris, New York and Chicago show that data can be used to deliver optimised rider experiences and grow Bike Share Schemes

LONDON, 8 November 2017 – Stage Intelligence, the leading provider of Bike Share Scheme management solutions, has released its 2016 Q4 data on bicycle and docking station usability and availability across Bike Share Schemes in London, Paris, New York and Chicago. Usability is central to providing an exceptional rider experience and supporting the growth of Bike Share Schemes. It ensures bikes and docking stations are available when and where they are needed most.

The data reveals Chicago and London leading the group with an average usability figure for the quarter of 99.3% and 99.4% respectively. Chicago has been consistent in delivering a reliable Bike Share Scheme to its riders. London is also rated highly but this could indicate over servicing its market, which can create unnecessary costs and limit growth.

New York City ranks the lowest of the major cities with an average usability figure of 90.2% for the quarter. It means that on average 10% of riders at any given time cannot access the bikes or docking stations they want. Paris follows New York City with an average usability of 98.1% with usability dipping to lows of 76.7%. The inconsistency in the scheme means that it may be difficult for riders to depend on the scheme on a daily basis.

“Bike Share riders and cities benefit from Schemes that are easy and reliable to use,” said Tom Nutley, Head of Operations at Stage Intelligence. “Operators need to make sure that riders have access to bikes when and where they need them without over servicing the market. This is where the London scheme could be at most risk. The data is very positive for London but it could be using too much city resources to manage its operations especially when there is no need to.”

Stage’s usability measure compares all docking stations that are within easy walking/cycling distance in a published 500m radius from each other, which can be altered by the BICO platform. The platform takes into account each city’s SLAs when measuring the usability of a Bike Share Scheme. A docking station is usable if there are bikes and docking points available at the station itself or at one or more of its neighbours. The BICO platform can also set custom usability defined by a specific threshold or the SLAs of different cities.

“For Bike Share schemes to be seen as a real, public transport solution and a smart answer to urban mobility, they need to work as good or better than existing public transport services,” said Paul Stratta, Director, at Platform for European Bicycle Sharing & Systems (PEBSS), an initiative from the ECF. “Nowadays people go to bus and railway stations expecting the services to be there, and for it to operate on time. It should be the same with Bike Share schemes. Collecting and analysing data allows Bike Share operators, and their city clients, to get a big picture of operations and understand where bike share can improve and how exactly to do it.”

The neighbourhood approach goes beyond the usual cluster and geographic data collection method which may be a sub-optimal approach – especially in larger schemes. It can identify if Bike Share Schemes are managed well and if it is over or under servicing the cities and its riders. The BICO platform is dynamic to each city and considers each city’s user patterns and prioritisation as well as the SLAs they operate under to measure the usability of Bike Share Schemes and provide valuable data for operators.

“Our BICO platform allows us to take a deep dive into individual Bike Share Schemes in different cities and neighbourhoods around the world and find ways to improve usability within them,” said Toni Kendall-Troughton, CEO at Stage Intelligence. “We were particularly impressed with Chicago’s Bike Share scheme which was performing well without over servicing its neighbourhoods or the market. It was consistent throughout the quarter with high usability figures and over-performed on busy summer weekends to meet the rise in demand.”

About Stage Intelligence

Stage Intelligence specialises in developing Artificial Intelligence solutions for the transport and logistics industry. Its flagship solution, the BICO recommendation engine, delivers real-time intelligence for the management of bikeshare schemes. BICO enables precise and optimal decision making and has been purpose-built to remove the complexity from managing resources within a bikeshare scheme. Customers choose Stage Intelligence because our solutions increase their agility, adaptability and enable them to move beyond traditional manual processes. We collaborate with customers to solve complex problems and deliver solutions that have a lasting impact on their operations.

Cities and its citizens stand to gain a lot from the success of Bike Share Schemes. They provide a clean and healthy transportation option in increasingly congested urban areas. Cities now play a huge role in attracting new schemes and supporting the adoption with cyclists.

In an effort to grow and capture further market share, Bike Share Schemes are always looking to enter new markets. Chinese start-ups are a prime example of this with many expanding to nearby countries such as Singapore and even as far as the UK.

Operators are now looking at more than just market size. They need to be sure that cities can fully support the growth of their schemes with proper infrastructure, capital and in changing consumer perception if necessary.

We highlight what cities and city planners can do to help attract Bike Share Schemes and support the adoption and growth with its citizens:

Provide safe cycling infrastructure:

It is important that citizens have access to safe cycling infrastructure. By promoting safe cycling, more riders are likely to see Bike Share Schemes and cycling in general as a viable solution.

Suitable cycling lanes and places for docking stations will be critical to the adoption and growth of the schemes.

Promote a cycling culture

The citizens are one of the biggest assets for cities. By changing perceptions and encouraging people to cycle, Bike Share Scheme operators will see more value and potential in entering the market.

Aside from getting operators into the market, a cycling culture will also greatly benefit the city. As more people cycle, the image of cities itself can be reshaped while seeing environmental and cost benefits.

Work with existing transportation hubs

A huge amount of Bike Share Scheme riders see it as a last-mile solution. Such schemes often help them get to their final destinations quicker, easier and more cost efficiently.

Through working with existing hubs by strategically placing bikes and docking stations, operators will have access to a large portion of the market. Cities can also offer its citizens an integrated transportation option.

Partner with operators

By working with operators, cities can ensure that Bike Share Schemes are set up to meet both the needs of the cities and citizens as well as the operators themselves. Showing a willing partnership is going to be more encouraging to new operators looking to enter and grow in a specific market.

Cities also have immense potential in capturing data. Operators need to make use of the data available in cities to increase ridership. Data within cities can be used to identify key areas that will be crucial to new schemes and is also highly helpful in predicting demand.

At Stage Intelligence, we use real-time data available in cities and Artificial Intelligence technology to simplify Bike Share Scheme logistics. By understanding the data, Bike Share Schemes can remove complexity and give bikes to riders when and where they want them.

To find out more about how Stage Intelligence can manage operations and increase ridership within your Bike Share Scheme, please contact

As Bike Share Schemes around the world become more popular, how we manage the resources such as bikes and docking stations defines the success and growth of such programs.

For Bike Share Schemes to truly be a solution to last mile problems, riders need bikes and docking stations to be available when and where they need them. It is up to the operators to ensure this happens every time.

But many operators fail to provide this basic level of service as they lack the actionable data and operations to manage the schemes effectively.

For a long time, the solution to ridership problems in Bike Share Schemes has been to supply the market with more bikes. In reality this does little to increase efficiency and often adds to the problem.

Mobike’s ‘Magic Cube’, uses data and AI to forecast supply and demand for its bike-rentals. In a fierce competition for market share, Mobike is seeing the value of using AI to simplify scheduling and operations of its scheme.

The importance of data and AI is clear. For operators, the key is in not only collecting the data but also having a process that works with its systems and resources to drive growth and increase ridership.

In the future, we are going to see more operators turn to data and AI, especially since cities have the potential to collect and store vast amounts of valuable data. With actionable data, operators save money, cities aren’t cluttered with bikes and citizens can rely on a reliable Bike Share Scheme that they can use in their day-to-day lives.

At Stage Intelligence, we have been using Artificial Intelligence (AI) and self-organising algorithms to solve complex problems in Bike Share Schemes from the beginning. Our BICO solution is easily incorporated into existing platforms to simplify logistics and increase ridership.

As increasing number of people look to get healthier, save money and time and preserve the environment, it’s no surprise that Bike Share Schemes are growing in popularity around the world.

With traditional schemes doing well in many cities, more and more start-ups are bringing out dockless Bike Share Schemes in the hope to take advantage of the rising on-demand culture. It gives riders convenience, choice and transparency over the more traditional docked schemes.

With a free-flowing Bike Share Scheme, riders can use their smartphones to find, pay for and unlock bikes and leave the bike anywhere once they are done. It’s this level of simplicity that is making such schemes very popular.

In fact, in China, the most mature market for Bike Share Schemes, start-ups have had massive success entering the market, raising significant amount of funding and supplying vast amounts of bikes.

At the same time, the news in this market dominates around dockless bikes being stolen, damaged and left in an unsuitable place by their millions. For operators, they are constantly replacing bikes while cities and its citizens are seeing more cluttered bikes on their streets.

This raises the question; which schemes should cities adopt? Free-flowing Bike Share Schemes are a topic of heavy debate for many cities due to the problems they can create if it remains unmanaged. The solution for many companies was to supply more bikes to the market, which only added to the problem.

But operators are now becoming savvier. They are offering parking spaces, rewards for good riders and improved apps to track their bikes. This is a step in the right direction to tackling the problem. With dockless bikes being a good way to get people cycling, it would be wrong to completely rule out the free-flowing schemes.

Instead, operators should focus on how they can effectively manage existing resources to benefit themselves, the cyclists and cities. By effectively managing logistics, operators can remove bikes from overcrowded and unsuitable areas to supply it to areas that need them.

Through collecting and organising huge amounts of data available in cities, operators gain real insight into their schemes as well as the market. They gain cost efficiencies as they are not unnecessarily purchasing bikes and riders can trust that bikes are available when and where they need them.

At Stage Intelligence, we use close to infinite amount of data and Artificial Intelligence technology to offer a simple management process for Bike Share Schemes. By predicting demand and managing supply, operators see real benefits to their schemes.

2016 marked a turning point for Artificial Intelligence (AI) in the transportation industry. We are seeing ideas that seemed distant actually becoming a reality. Self-driving cars are on the roads, Mobility as a Service (MaaS) apps are going live and we have deployed our AI-based technology in Bike Share Schemes around the world.

The industry is at the very beginning of a period of rapid change. Throughout 2016, we’ve seen glimpses of the future that have hinted at what is possible in transportation. Legacy models are being challenged and there is an appetite for change. Read more